Eco-environmental changes due to human activities in the Erhai Lake Basin from 1990 to 2020

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit–based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995–2000, 2000–2005, 2005–2009 and 2015–2020, and the improvement was most significant in 1995–2000, covering an area of 823.95 km2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.


SPWI
The SPWI is an indicator for the spatial distribution of surface water flow and provides insights into the influence of water on the ecological environment.It enhances the reliability of EEQ assessments in proximity to water bodies 26,35 and is calculated as follows: where ρ Blue , ρ NIR and ρ SWIR2 are the reflectance values of the blue, thermal infrared and second short-wave infrared bands of Landsat images, respectively.NDLI Urban air humidity considerably influences the characterisation of the internal climate of urban areas.Their impact on the urban ecosystem can be determined by investigating their correlation 36 .In this study, the NDLI was used to represent the urban air humidity 37 ; it is calculated using Eq. ( 2):  where ρ Green , ρ Red and ρ SWIR1 are the reflectance values of the green, red and first short-wave infrared bands, respectively.

LST
The urban heat island considerably influences the urban ecological environment, and its impact can be determined based on the LST 9 .Herein, the LST was retrieved using the emissivity modulation (EM) method 38,39 as follows (Eqs.( 3), ( 4), ( 5), ( 6)): where T b and λ are the brightness temperature and central wavelength (μm) of the thermal infrared band, ε is the surface emissivity, ρ = 1.438 × 10 −2 (mK), P v is the vegetation coverage, NDVI max and NDVI min are the maximum and minimum values of NDVI, respectively, and ρ NIR and ρ Red are the surface reflectance values in the near- infrared and thermal infrared bands, respectively.

RVI
The RVI effectively depicts vegetation coverage while mitigating discrepancies arising from various soil backgrounds and shadows 40 .Herein, the RVI was used to indicate the impact of regional human activities on the ecological models within regional boundaries; it is calculated using Eq. ( 7): (2) Flowchart of image processing and analysis. Vol.:(0123456789)

NDSI
In addition to vegetation cover, changes in impervious surface area can directly reflect the intensity of human activities on the ecological environment 41 .Herein, the NDSI, which is responsive to impervious surfaces, was used to determine the impact of human activities on the ecological environment 42 and is calculated using Eq. ( 8): where ρ NIR and ρ SWIR1 are the reflectivity values of the near-infrared and first short-wave thermal infrared bands, respectively.

Corrected entropy weight coefficient method
Information entropy is a measurement index used to quantitatively describe the degree of information uncertainty and has been widely used in information fusion 43 .Herein, it was used to evaluate the information richness of each ecological indicator and the degree of information difference among the indicators.Each indicator was then assigned an appropriate weight 44 .
First, the weight of each indicator was calculated using the corrected entropy weight coefficient method 45 as follows: where w j and e j denote the weight and entropy for each ecological indicator j, respectively, m is the number of ecological indicators, f ij is the proportion of pixel i in each ecological indicator j, n is the number of all pixels in each ecological indicator j and x ij is the reflectivity of pixel i in each ecological indicator j.
As each indicator has a different unit and numerical range, their direct fusion will cause an imbalance of the indicator weight value 9 .Therefore, the values of the five indicators must be normalised to fall within [0,1] before fusion as follows: where N j is the standardised value of N i , N max and N min represent the maximum and minimum values of each indicator, respectively.
The WBEI was then acquired by linear superposition and fusion of the weight value and the corresponding ecological indicator as follows: where NDLI, RVI and SPWI are positive indicators.LST and NDSI are negative indicators.w 1 , w 2 , w 3 , w 4 and w 5 are the weight values of the NDLI, RVI, SPWI, LST and NDSI, respectively.N NDLI , N RVI , N SPWI , N LST and N NDSI are the normalised values of the NDLI, RVI, SPWI, LST and NDSI, respectively.

WBEI performance validation
Herein, the spatial coverage sampling method 46 was used to evenly select 2000 points in the Erhai Lake Basin in 2020, and the WBEI performance for both water bodies and land areas was evaluated.
In the land area, the improved RSEI 18 and CEEI 19 , which can quickly and accurately assess the improvement in regional terrestrial EEQ , were used to validate the performance of WBEI.
where PC1 is the first component of PCA, f is the positive normalisation of the four indicators and V NDVI , V Wet , V NDSI and V LST are the eigenvectors of the NDVI, Wet 47 , NDSI and LST, respectively.VC is the vegetation coverage, VHI is the vegetative health index, NDSI is the normalised differential build-up and bare soil index 9 and LSM is the land surface moisture.More detailed information about the RSEI and CEEI can be found in the study reported by Ning et al. 18 and Yang et al. 19 .
In the water area, the trophic level index (TLI) 48 was used to comprehensively validate the performance of WBEI in determining the EEQ.
where x is the ratio of the near-infrared band to infrared band and C chl−a is the chlorophyll-a concentration in the water area.

WBEI classification and EEQ change detection
Based on the principle that a higher value of EEQ (closer to 1) indicates a better ecological environment and by considering the mean and standard deviation of WBEI, the WBEI values were categorised into five ecological quality levels 49 (Table 2).A transition matrix was used to describe the EEQ changes in the Erhai Lake Basin from 1990 to 2020 50 (Table 3).

Kernel density estimation
Kernel density estimation (KDE) is a non-parametric method used to estimate the probability density function.It calculates the density distribution of points and line elements in space in their surrounding fields using a kernel function and reflects the distribution characteristics of spatial elements with the kernel density value of each grid in a continuous simulation image 51 .
where f n (x) is the estimated value of the probability density; n is the number of observations; h is the bandwidth, which is the extended width of x in space and directly affects the precision of the kernel density result; K(•) is the kernel function and x − X i is the distance from x to sample X i .

WBEI model performance
To objectively assess the effectiveness of WBEI for EEQ assessment, distinct evaluation models were used for both land areas and water bodies.The correlation coefficients between the WBEI and RSEI as well as WBEI and CEEI were determined for land areas (Fig. 3), whereas that between the WBEI and TLI was determined for water bodies to assess the WBEI performance (Fig. 4).Thus, the WBEI had a strong correlation with the RSEI and CEEI in land areas, with R 2 values of 0.785 and 0.842, respectively.It demonstrated a good correlation with TLI in water bodies (R = 0.733), with an R 2 value of 0.538.These findings indicate that the WBEI can assess the quality of terrestrial ecological environments and water area ecological environments to a certain extent.

Validation of the SPWI
To validate the ability of SPWI to characterize water spatial distribution, this study compared three different levels of water abundance in Erhai Lake, urban construction areas and ponds based on the Wet index 47 , which is widely ( 16) 2. Classification of the EEQ in the Erhai Lake Basin.x and s represent the average value and standard deviation of the WBEI of EEQ from 1990 to 2020, respectively.

Types
Poor Fair Moderate Good Excellent Table 3. Transition matrix of the EEQ in the Erhai Lake Basin.T 1 and T 2 represent the beginning and ending years of each period, respectively.used to evaluate regional EEQ.As shown in Fig. 5, in region (I) (Erhai Lake), the normalised SPWI results were consistent with the normalised Wet Index results, both indicating high water abundance.However, in region (II) (urban construction area), the water content abundance is extremely poor, whereas the Wet index results yielded high values, whereas SPWI yielded the opposite results.In addition, the water content abundance of region (III) (pond) should be much lower than that of region (I) (Erhai Lake), the values of the two regions were the same in the wet index results, while SPWI could effectively distinguish between the water abundance levels of the two regions.In summary, SPWI can better reflect the abundance of surface water resources in the Erhai Lake Basin.

WBEI analysis
The average values of WBEI and the weights of each ecological factor from 1990 to 2020 were obtained using the GEE (Table 4).Based on the average WBEI value, the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound.Specifically, the changes in WBEI from 2009 to 2020 aligned with the changes in water resources monitored by the local water conservancy department 52 .This further confirmed the correlation between water factors and the regional ecological environment.Moreover, the weight of the water ecological indicator exhibited an initial improvement followed by degradation from 1990 to 2020, indicating significant fluctuations in the environmental water quality in the Erhai Lake Basin.The trend for LST weight from 1990 to 2020 was contrary to that for NDLI, in line with the explanation that LST decreases due to the cooling effect of evapotranspiration 37 .In terms of land cover, the combined weights of the RVI and NDSI exhibited a fluctuating upward trend, suggesting an increased responsiveness of land cover to the urban ecological environment in the Erhai Lake Basin over the past 30 years.This indicates that impervious surfaces encroached upon the natural landscape in the Erhai Lake Basin from 1990 to 2020.

Changes in the EEQ
The spatiotemporal characteristics of the EEQ in the Erhai Lake Basin from 1990 to 2020 were derived from the WBEI classification results (Fig. 6), and the area and proportion of the EEQ classification were quantified (Table 5).The changes in the EEQ for each year were detailed from the perspectives of land areas and water bodies (Fig. 7).In general, from 1990 to 2020, the Erhai Lake Basin primarily contained regions with fair, moderate  and good EEQ levels, accounting for more than 20%.Additionally, regions with poor and fair EEQ levels were primarily concentrated around Erhai Lake characterised by high urbanisation levels and relatively flat terrain.
The Erhai Lake Basin exhibited lower EEQ levels in 1995 than in other years (Tables 4 and 5).A poor EEQ level was observed over an area of 130.99 km 2 , mainly concentrated along the eastern coast of Erhai Lake (Fig. 6).Specifically, the proportion land and water regions with poor EEQ levels accounted for 5.62% and 0.02% of the total land area and water body, respectively (Fig. 7).Meanwhile, areas with poor and good EEQ levels were the largest, reaching 1086.78 km 2 (41.92%) and 740.50 km 2 (28.57%), respectively (Table 5).The Erhai Lake Basin exhibited higher EEQ levels in 2009 than in other years.Excellent EEQ levels were observed across areas of 337.36 km 2 , accounting for 13.01% of the total area (Table 5), primarily concentrated in Erhai Lake and the Cangshan Mountain region characterised by lower levels of human activity (Fig. 6).Among them, the proportion of land and water with excellent EEQ levels accounted for 10.79% and 32.83% of the total land and water areas,  respectively (Fig. 7).Previous studies have also confirmed our findings.Specifically, in the land regions from 1999 to 2019, lower EEQ values were predominantly clustered around Erhai Lake, which experienced intense human activity.Conversely, higher EEQ values were primarily concentrated in the western and southern parts of the study area, notably in the Cangshan region situated in the western segment of the Erhai Lake Basin 30,31 .

Monitoring of dynamic changes in EEQ in the Erhai Lake Basin
The EEQ changes in the Erhai Lake Basin from 1990 to 2020 were calculated using the transition matrix (Tables 6, 7 and Fig. 8), and a search radius of 1000 m was selected for KDE to visualise the spatial patterns of EEQ changes (Fig. 9 and 10).In general, the EEQ in the Erhai Lake Basin tended to deteriorate in 1990-1995 and 2009-2015 (Table 4).The areas (percentage) of deterioration were 567.72 km 2 (21.90%) and 655.73 km 2 (25.30%), respectively; these regions were mainly distributed around Erhai Lake (Fig. 10), particularly on its western coast.4), with the largest improvement in 1995-2000 across 823.95 km 2 , accounting for 31.79% of the total basin area.This area was concentrated in the southwest of the Erhai Lake Basin, particularly in the Cangshan Mountain region (Fig. 10).In addition, the improved area exceeded twice the deteriorated area in 2000-2005, 2005-2009 and 2015-2020 (Table 7).

Driving forces of the EEQ changes in the Erhai Lake Basin
The changes in EEQ in the Erhai Lake Basin were mainly influenced by a combination of anthropogenic and natural factors, with human activities and policy variations playing dominant roles 53 .This study conducted principal component analysis (PCA) on five indices (see Supplementary Table S1), revealing that the NDSI, which represents the intensity of human activities, exhibited the highest comprehensive contribution in the first principal component (PC1).This indicated that human activities and policy factors are the predominant drivers of EEQ changes in the Erhai Lake Basin, consistent with previous research findings 30,53 .Additionally, natural factors, such as climate, belong to the realm of macroscopic regulation and cannot be controlled, while anthropogenic factors, such as human activities, can be assessed and controlled through the mutual feedback between humans and the ecological environment 54 .Consequently, this study primarily analysed the influence of human activities and policy changes on the trends of EEQ changes.Since the 1970s, the urbanisation rate in the Erhai Lake Basin has continuously increased.Moreover, human activities in the basin have remained consistently active, causing ecological environmental damage 55 .In 1990, 93.58 km 2 (3.61%) and 1031.71km 2 (39.80%) of areas exhibited poor and fair EEQ levels, respectively (Table 5).Furthermore, the fishery has considerably increased in Dali City since 1993, and artificial fish feed is directly dispersed into Erhai Lake.This has deteriorated the water quality and increased the total nitrogen (TN) and total phosphorus (TP) concentrations 56 , leading to deteriorated EEQ.
The deteriorating ecological environment has affected the quality of life; thus, the importance of protecting the ecological environment to enhance the quality of life has been gradually recognised.The local government in China, with support from the United Nations Environment Programme (UNEP) and the United Nations Development Programme (UNDP), implemented 'Investment Planning and Capacity Building for Sustainable Development of Erhai Lake Basin' in 1995-1996.Since 2000, the Erhai Lake Basin has actively promoted tourism, leveraging its beautiful alpine lake scenery and distinctive ethnic culture.This has mitigated ecological degradation caused by agricultural and industrial development 57 , resulting in an overall improvement in the EEQ in the Erhai Lake Basin in 1990-2009.However, the absence of planning and delayed infrastructure development in the early rural areas around Erhai Lake has led to the rapid proliferation of hotels, inns and restaurants, resulting in disorderly and extensive development, as well as ecological degradation in non-coal mine 28,29 .Consequently, the EEQ in the Erhai Lake Basin seriously deteriorated from 2009 to 2015.
Fortunately, under the guidance of the Government of China to protect the ecological environment of the Erhai Lake Basin, the local government has proactively implemented a series of measures since the end of 2015.These measures include the establishment of sewage treatment plants, closure of mines, rectification of illegal construction works, and the formulation of a series of protection and treatment policies.On 30 May 2018, Dali City announced the 'Three-line Delineation Plan for Ecological and Environmental Protection of Erhai Lake' that defines the key management areas for water ecological protection.In May 2020, the government of the Dali Bai Autonomous Prefecture approved the implementation of the 'Erhai Lake Protection and Governance Plan (2018-2035)' .This plan aims to provide directions for the protection and management of the Erhai Lake Basin, adopting a systematic and holistic approach to restore the lake basin and establish an ecological security barrier.As a result, due to the promotion and policy influence of local government departments, the EEQ in the Erhai Lake Basin considerably improved from 2015 to 2020.

Development of ecological quality conservation measures
Water bodies, such as Erhai Lake and rivers, are crucial components of the Erhai Lake Basin.The water quality of these bodies is a key factor influencing the ecological environment within the basin.Therefore, considering the water bodies is helpful for a more comprehensive quantification of the EEQ within the Erhai Lake Basin.This, in turn, is of great significance for formulating effective measures to promote the sustainable development of the region.Based on the EEQ assessment results of the Erhai Lake Basin from 1990 to 2020 and the characteristics  of the Erhai Lake Basin, this study proposes the following suggestions: (1) building a robust ecological security barrier, optimizing the urban green space pattern, and promoting sustainable development; (2) enhancing the effectiveness of the "Erhai Lake Protection and Governance Plan," including strengthening the construction of sewage treatment facilities, regulating the construction of hotels, restaurants, and other establishments, and enhancing publicity for Erhai Lake protection; (3) utilizing remote sensing and geographic information technology to establish a specialised monitoring system for the ecological environment management of the  Erhai Lake Basin, achieving dynamic, effective, quantitative monitoring and evaluation, and providing rapid and timely feedback.

Limitations and future works
Herein, the WBEI and EEQ in the Erhai Lake Basin were validated and determined, respectively, from 1990 to 2020; however, some limitations exist.Firstly, an empirical model was used to estimate the TLI.However, water bodies in plateau lakes exhibit highly complex water compositions and distinct regional characteristics 58 .In addition to chlorophyll-a, water transparency, TN and TP should be used to evaluate water quality 59 .These may be the reasons for the low correlation coefficient between the EEQ and TLI of water bodies.Secondly, the results of SG filtering were used to fill in the missing data.However, the details preserved after SG filtering may include abnormal information 60 , potentially introducing errors in the filled results.
For future studies, the combination of water transparency, chlorophyll-a, TN and TP should be considered to calculate TLI, further evaluate the performance of WBEI in assessing the EEQ of water bodies.WBEI could consider more water spectrum of different regions for improving the applicability of evaluating water EEQ.And more effective filtering methods such as weighted Whittaker smoother 60 could be considered.

Conclusions
In this study, the performance of WBEI in the EEQ assessment in land areas and water bodies was evaluated.Then, the spatiotemporal evolution characteristics of the EEQ from 1990 to 2020 in the Erhai Lake Basin were quantitatively analysed using WBEI, and the driving factors of the EEQ evolution were revealed.The spatiotemporal evolution characteristics of the EEQ exhibited a trend of initial degradation, subsequent improvement, further degradation and a rebound.The regions with poor and fair EEQ levels were mainly concentrated around Erhai Lake, which has a high urbanisation level and relatively flat terrain.Among them, the EEQ levels in 1990, 1995 and 2015 were not optimistic, and the regions with unsatisfactory EEQ (poor and fair) levels accounted for 43.41%, 47.01% and 40.05% of the total basin area, respectively.The EEQ level improved in 1995-2000, 2000-2005, 2005-2009 and 2015-2020.The improved area was the largest from 1995 to 2000, covering 823.95 km 2 and accounting for 31.79% of the total basin area.By analysing the data on the EEQ in the Erhai Lake Basin from 1990 to 2020 and the planning documents of the local government on the management of the region, we confirmed that the EEQ was primarily affected by human activities and policy variations.The findings of this study can serve as a scientific basis for formulating sustainable development policies and the planning and management of the Erhai Lake Basin.

Figure 1 .
Figure 1.Location of the Erhai Lake Basin.(a) Study area in China, (b) study area in Yunnan Province and (c) elevation of the study area.The figure is created used ArcMap 10.7, https:// www.arcgis.com.

Figure 5 .
Figure 5. Spatial distribution of water obtained from (a) original false-color image, (b) Wet results, and (c) SPWI results.

Figure 6 .
Figure 6.Spatiotemporal characteristics of the EEQ in the Erhai Lake Basin from 1990 to 2020.

Figure 7 .
Figure 7. Changes in the EEQ levels of land areas and water bodies in the Erhai Lake Basin from 1990 to 2020.(a) Land and (b) water.

Figure 8 .
Figure 8. Sankey diagram of the EEQ changes in the Erhai Lake Basin from 1990 to 2020.

Figure 9 .
Figure 9. Kernel density distribution of EEQ improvement in the Erhai Lake Basin from 1990 to 2020.

Figure 10 .
Figure 10.Kernel density distribution of EEQ deterioration in the Erhai Lake Basin from 1990 to 2020.

Table 1 .
Experimental data collection.

Table 4 .
Average values of the WBEI and the weight of each ecological factor from 1990 to 2020.

Table 5 .
EEQ levels in the Erhai Lake Basin from 1990 to 2020.

Table 6 .
Transition matrix for the EEQ in the Erhai Lake Basin from 1990 to 2020.

Table 7 .
EEQ changes in the Erhai Lake Basin from 1990 to 2020.